MLA-C01 Data Preparation for Machine Learning Practice Question
A company is preparing data for a time-series forecasting model. The data is collected from IoT sensors at irregular intervals. Which TWO steps are necessary to prepare the data? (Choose 2.)
⚠ Common exam trap
AWS often tests the misconception that data normalization or outlier removal is a universal first step, but for time-series with irregular intervals, the critical preparatory steps are resampling and handling missing values to create a regular time grid.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Resample the data to a fixed frequency
Time-series forecasting models require data at consistent time intervals to capture temporal patterns and seasonality. Resampling the irregular IoT sensor data to a fixed frequency (e.g., every 5 minutes) creates a uniform time index, which is essential for algorithms like ARIMA, Prophet, or LSTM. This step ensures the model can learn from a structured sequence rather than being confused by variable time gaps.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Normalize the data to a 0-1 range
Why it's wrong here
Normalization may be needed for some models but is not always necessary.
- ✓
Resample the data to a fixed frequency
Why this is correct
Resampling creates regular time intervals required by most forecasting models.
- ✓
Fill missing values using forward fill or interpolation
Why this is correct
Irregular intervals often result in missing timestamps; filling them is necessary.
- ✗
Remove outlier data points
Why it's wrong here
Outlier removal is not a required step for all time-series models.
- ✗
Encode categorical features
Why it's wrong here
No categorical features are mentioned; this is not a necessary step.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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